1. Field of the Invention
The present invention relates to identification of articles on a production line or the like, and more particularly to apparatus for learning a characterization of an object and thereafter identifying the presence and orientation of the object for control of robotic systems.
2. Description of the Prior Art
With the continuing automation of manufacturing processes which includes automatic assembly of products, there is a need for apparatus to control robotic arms and other automatic machinery. For example, a part may be being carried to a point of assembly and thereafter be grasped by a robotic arm and placed in the proper location on the product by the arm. The assembly system must first be able to recognize the presence of the part and also its orientation since generally there is only one orientation with respect to the device being assemblied for which the part will fit. In many cases, human labor is used to identify and orient parts for subsequent automatic installation or assembly.
Apparatus is known in the art which can, through the use of video techniques, identify objects using gray scale techniques. For example, the GVS-41 system originally developed for the military has been used in the past for this purpose. Although it is known to use the GVS-41 system for robotic control systems, there have been problems in operating under difficult and variable lighting conditions which is particularly important in factory environments where lighting control is usually impractical.
The following papers are known which relate to the problem of identifying parts and guiding robotics:
L. M. Sweet et al, "Processing of Contour and Binary Images for Vision-Guided Robotics", Conference on CAD/CAM Technology in Mechanical Engineering, MIT, Cambridge, Mass., March, 1982 PA0 W. A. Perkins, "A Model-Based Vision System for Industrial Parts", IEEE Transactions on Computers, Vol. C-27, 1978 PA0 K. E. Price, "Matching Closed Contours", Seventh International Conference on Pattern Recognition, Montreal, Canada, July, 1984 PA0 S. G. Akl and G.T. Toussaint, "Efficient Convex Hull Algorithms for Pattern Recognition Applications", National Research Council of Canada
There is a need for a system which will permit a vision system such as a GVS-41 to quickly learn the characteristics of a part in an off-line mode, and to thereafter in an on-line mode recognize the part and its orientation. Such a system then should then be able to control a robotic arm to grasp the part and reorient to the required position.